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          <h1 class="post-title" itemprop="name headline">GIS算法基础（八）基于距离变换的栅格骨架提取算法

            
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              <time title="创建时间：2018-12-16 19:28:19" itemprop="dateCreated datePublished" datetime="2018-12-16T19:28:19+08:00">2018-12-16</time>
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        <h1 id="一、为什么需要骨架提取"><a href="#一、为什么需要骨架提取" class="headerlink" title="一、为什么需要骨架提取"></a>一、为什么需要骨架提取</h1><p>简单来说就是用于细化栅格，便于栅格数据转换为矢量数据</p><p>栅格格式向矢量格式转换是提取相同编号的栅格集合表示的边界，栅格点转换成矢量点，很简单，在坐标系确定的情况下通过解析式可以直接转换。而线与面在转换成矢量的时候，本质上都是在提取边界或中轴线，因此在栅格中提取中轴线就与栅格的细化的关系密不可分，这是因为线状栅格数据一般具有粗度且线条本身往往呈现粗细。栅格数据需要细化，以提取中轴线。这是因为：</p><a id="more"></a>

<p>①中轴线是栅格数据曲线的标准化存储形式</p>
<p>②实现细化是将栅格曲线矢量化的前提</p>
<p>③在有些算法中可以提高计算精度</p>
<p><img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205749.png!blog" alt="20190907205749"><img src="" alt="点击并拖拽以移动"></p>
<h1 id="二、距离变换法提取骨架"><a href="#二、距离变换法提取骨架" class="headerlink" title="二、距离变换法提取骨架"></a>二、距离变换法提取骨架</h1><h2 id="距离变换图"><a href="#距离变换图" class="headerlink" title="距离变换图"></a>距离变换图</h2><p>距离变换图也是一种栅格图像，其中，每个像元值存储了它到栅格图上相邻物体的最近距离。这个距离的量度：可以是曼哈顿距离，棋盘距离，或者欧式距离。这三个距离关系在GIS中很常用。算法实现如下：</p>
<figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/**</span></span><br><span class="line"><span class="comment"> * </span></span><br><span class="line"><span class="comment"> * <span class="doctag">@param</span> disType 距离类型</span></span><br><span class="line"><span class="comment"> * <span class="doctag">@param</span> s1 像元1</span></span><br><span class="line"><span class="comment"> * <span class="doctag">@param</span> s2 像元2</span></span><br><span class="line"><span class="comment"> * <span class="doctag">@return</span></span></span><br><span class="line"><span class="comment"> */</span></span><br><span class="line"><span class="function"><span class="keyword">private</span> <span class="keyword">double</span> <span class="title">calculateDis</span><span class="params">(DisType disType,Pixel s1,Pixel s2)</span> </span>&#123;</span><br><span class="line">	<span class="keyword">double</span> dis = <span class="number">0</span>;</span><br><span class="line">	<span class="keyword">switch</span> (disType) &#123;</span><br><span class="line">	<span class="keyword">case</span> Euclidean:</span><br><span class="line">		dis = Math.sqrt(Math.pow(s1.getRow()-s2.getRow(), <span class="number">2</span>)+Math.pow(s1.getColumn()-s2.getColumn(), <span class="number">2</span>))*size;</span><br><span class="line">		<span class="keyword">break</span>;</span><br><span class="line">	<span class="keyword">case</span> CityBlock:</span><br><span class="line">		dis = Math.abs(s1.getRow()-s2.getRow())+Math.abs(s1.getColumn()-s2.getColumn())*size;</span><br><span class="line">		<span class="keyword">break</span>;</span><br><span class="line">	<span class="keyword">case</span> ChessBoard:</span><br><span class="line">		dis = Math.max(Math.abs(s1.getRow()-s2.getRow()), Math.abs(s1.getColumn()-s2.getColumn()))*size;</span><br><span class="line">		<span class="keyword">break</span>;</span><br><span class="line">	<span class="keyword">default</span>:</span><br><span class="line">		dis = Math.sqrt(Math.pow(s1.getRow()-s2.getRow(), <span class="number">2</span>)+Math.pow(s1.getColumn()-s2.getColumn(), <span class="number">2</span>))*size;</span><br><span class="line">		<span class="keyword">break</span>;</span><br><span class="line">	&#125;</span><br><span class="line">	<span class="keyword">return</span> dis;</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>

<p><img src="" alt="点击并拖拽以移动"></p>
<h2 id="基于距离变换法提取骨架算法思想："><a href="#基于距离变换法提取骨架算法思想：" class="headerlink" title="基于距离变换法提取骨架算法思想："></a>基于距离变换法提取骨架算法思想：</h2><p>对内部点集i到非内部点集e（孤立点与边界点）求最小距离，实际上就是求目标点到最近背景点的距离（背景点-值为0的像元  目标点-值为1的像元），求出距离后 对距离进行分类即可得骨架图</p>
<h2 id="基于距离变换法提取骨架算法步骤："><a href="#基于距离变换法提取骨架算法步骤：" class="headerlink" title="基于距离变换法提取骨架算法步骤："></a>基于距离变换法提取骨架算法步骤：</h2><p>①将栅格图像进行初始二值化（背景点设为0，目标点设为1）</p>
<p>②将栅格图像进行分类，把栅格分为内部点，边界点，孤立点。</p>
<p>③求每一个内部点到非内部点的距离，距离值赋给栅格值</p>
<p>④对栅格图像进行二值化（距离大于1的栅格值设为1，小于等于1的设为0）</p>
<p>③重复②③④，终止条件为“若下一次栅格图像二值化结果全部为0”</p>
<h3 id="如何分类："><a href="#如何分类：" class="headerlink" title="如何分类："></a>如何分类：</h3><p>在步骤②中，如何把栅格分为内部点，边界点，孤立点？</p>
<p>以中心像素的四邻域为例，</p>
<p>1、如果中心像素为目标像素(值为1)且四邻域都为目标像素(值为1)，则该点为内部点。</p>
<p>2、如果该中心像素为目标像素，四邻域为背景像素(值为0)，则该中心点为孤立点。</p>
<p>3、其他情况则为边界点</p>
<p><img src="https://img-blog.csdn.net/20140112193215250?watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQvVHJlbnQxOTg1/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/SouthEast" alt="img"><img src="" alt="点击并拖拽以移动"></p>
<h3 id="分类代码实现"><a href="#分类代码实现" class="headerlink" title="分类代码实现"></a>分类代码实现</h3><figure class="highlight swift"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">//判断是边界点，内部点，孤立点</span></span><br><span class="line"><span class="comment">//前提：栅格已经二值化</span></span><br><span class="line"><span class="keyword">public</span> void setNeighbourhood() &#123;</span><br><span class="line">	internalPoints = new <span class="type">ArrayList</span>&lt;&gt;();</span><br><span class="line">	borderPoints = new <span class="type">ArrayList</span>&lt;&gt;();</span><br><span class="line">	<span class="keyword">for</span>(int i=<span class="number">0</span>;i&lt;<span class="type">ROW</span>;i++) &#123;</span><br><span class="line">		<span class="keyword">for</span>(int j=<span class="number">0</span>;j&lt;<span class="type">COLUMN</span>;j++) &#123;</span><br><span class="line">			<span class="comment">//假-0 真-1</span></span><br><span class="line">			boolean up=<span class="literal">true</span>,down=<span class="literal">true</span>,<span class="keyword">right</span>=<span class="literal">true</span>,<span class="keyword">left</span>=<span class="literal">true</span>;</span><br><span class="line">			<span class="comment">//判断点的上部是否为0</span></span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				</span><br><span class="line">				<span class="keyword">if</span>(data[i-<span class="number">1</span>][j].getValue()==<span class="number">0</span>) &#123;</span><br><span class="line">					up=<span class="literal">false</span>;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (<span class="type">Exception</span> e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				up=<span class="literal">false</span>;</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			<span class="comment">//判断点的下部是否为0</span></span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				<span class="keyword">if</span>(data[i+<span class="number">1</span>][j].getValue()==<span class="number">0</span>) &#123;</span><br><span class="line">					down=<span class="literal">false</span>;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (<span class="type">Exception</span> e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				down=<span class="literal">false</span>;</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			</span><br><span class="line">			<span class="comment">//判断点的左边是否为0</span></span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				</span><br><span class="line">				<span class="keyword">if</span>(data[i][j-<span class="number">1</span>].getValue()==<span class="number">0</span>) &#123;</span><br><span class="line">					<span class="keyword">left</span>=<span class="literal">false</span>;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (<span class="type">Exception</span> e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				<span class="keyword">left</span>=<span class="literal">false</span>;</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			<span class="comment">//判断点的右边是否为0</span></span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				</span><br><span class="line">				<span class="keyword">if</span>(data[i][j+<span class="number">1</span>].getValue()==<span class="number">0</span>) &#123;</span><br><span class="line">					<span class="keyword">right</span>=<span class="literal">false</span>;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (<span class="type">Exception</span> e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				<span class="keyword">right</span>=<span class="literal">false</span>;</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			<span class="keyword">if</span>(!up &amp;&amp; !down &amp;&amp; !<span class="keyword">left</span> &amp;&amp; !<span class="keyword">right</span>) &#123;</span><br><span class="line">				data[i][j].setType(type.isolated);</span><br><span class="line">				</span><br><span class="line">			&#125;<span class="keyword">else</span> <span class="keyword">if</span>(up &amp;&amp; down &amp;&amp; <span class="keyword">left</span> &amp;&amp; <span class="keyword">right</span>) &#123;</span><br><span class="line">				data[i][j].setType(type.<span class="keyword">internal</span>);</span><br><span class="line">				internalPoints.add(data[i][j]);</span><br><span class="line">			&#125;<span class="keyword">else</span> &#123;</span><br><span class="line">				data[i][j].setType(type.boundary);</span><br><span class="line">				borderPoints.add(data[i][j]);</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			</span><br><span class="line">		&#125;</span><br><span class="line">	&#125;</span><br><span class="line">	</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>

<p><img src="" alt="点击并拖拽以移动"></p>
<h3 id="测试结果："><a href="#测试结果：" class="headerlink" title="测试结果："></a>测试结果：</h3><p> <img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205708.png!blog" alt="20190907205708"><img src="" alt="点击并拖拽以移动"></p>
<p>B代表边界点，I代表内部点，孤立点未进行渲染</p>
<h3 id="基于距离变换法提取骨架算法实现"><a href="#基于距离变换法提取骨架算法实现" class="headerlink" title="基于距离变换法提取骨架算法实现"></a>基于距离变换法提取骨架算法实现</h3><p>我使用了3*3模板的快速距离变换。</p>
<p>按照从上到下，从左到右的顺序，遍历3x3的栅格图像</p>
<p><img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205657.png!blog" alt="20190907205657"></p>
<p><img src="" alt="点击并拖拽以移动"></p>
<p>但是有个问题是：如果在遍历过程中，碰到了栅格的边界怎么办，所以我写了对应的解决办法，即先确定快速距离变换遍历的范围，在开始遍历快速距离变换。</p>
<p>代码如下：</p>
<figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br><span class="line">78</span><br><span class="line">79</span><br><span class="line">80</span><br><span class="line">81</span><br><span class="line">82</span><br><span class="line">83</span><br><span class="line">84</span><br><span class="line">85</span><br><span class="line">86</span><br><span class="line">87</span><br><span class="line">88</span><br><span class="line">89</span><br><span class="line">90</span><br><span class="line">91</span><br><span class="line">92</span><br><span class="line">93</span><br><span class="line">94</span><br><span class="line">95</span><br><span class="line">96</span><br><span class="line">97</span><br><span class="line">98</span><br><span class="line">99</span><br><span class="line">100</span><br><span class="line">101</span><br><span class="line">102</span><br><span class="line">103</span><br><span class="line">104</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/**</span></span><br><span class="line"><span class="comment"> * 骨架图算法（距离变换法搜索中轴线）</span></span><br><span class="line"><span class="comment"> * 对内部点集i到边界点集e求最小距离</span></span><br><span class="line"><span class="comment"> * 实际上就是求目标点到最近背景点的距离</span></span><br><span class="line"><span class="comment"> * 背景点-值为0的像元  目标点-值为1的像元</span></span><br><span class="line"><span class="comment"> * 求出距离后 对距离进行分类即可得骨架图</span></span><br><span class="line"><span class="comment"> */</span></span><br><span class="line"><span class="function"><span class="keyword">public</span> <span class="keyword">void</span> <span class="title">getMinDis</span><span class="params">(DisType disType)</span> </span>&#123;</span><br><span class="line">	<span class="comment">//快速距离模板计算</span></span><br><span class="line">	<span class="comment">//从左至右，从上到下，顺时针寻找周围是否有边界点</span></span><br><span class="line">	<span class="comment">//如果有，则加入计算</span></span><br><span class="line">	<span class="comment">//如果没有，则扩大搜寻范围,最大范围到数组越界</span></span><br><span class="line">	<span class="comment">//最后得出最小距离</span></span><br><span class="line">	<span class="comment">//当前圈层数</span></span><br><span class="line">	<span class="keyword">if</span>(borderPoints==<span class="keyword">null</span> &amp;&amp; internalPoints==<span class="keyword">null</span>) &#123;</span><br><span class="line">		setNeighbourhood();</span><br><span class="line">	&#125;</span><br><span class="line">	<span class="keyword">for</span>(Pixel i:internalPoints) &#123;</span><br><span class="line">		List&lt;Double&gt; disList = <span class="keyword">new</span> ArrayList&lt;&gt;();</span><br><span class="line">		<span class="comment">//搜索范围</span></span><br><span class="line">		<span class="keyword">int</span> cicleNum = <span class="number">1</span>;</span><br><span class="line">		<span class="comment">//上下左右搜寻边界</span></span><br><span class="line">		<span class="keyword">int</span> up,down,left,right;</span><br><span class="line">		<span class="keyword">int</span> upLimit,downLimt,leftLimit,rightLimit;</span><br><span class="line">		upLimit = <span class="number">1</span>;</span><br><span class="line">		downLimt = ROW;</span><br><span class="line">		leftLimit = <span class="number">1</span>;</span><br><span class="line">		rightLimit = COLUMN;</span><br><span class="line">		<span class="comment">//确定遍历范围，防止边界溢出</span></span><br><span class="line">		<span class="keyword">for</span>(<span class="keyword">int</span> curCir=<span class="number">0</span>;curCir&lt;cicleNum;curCir++) &#123;</span><br><span class="line">			<span class="keyword">try</span> &#123;	</span><br><span class="line">				up = i.getRow()-cicleNum;</span><br><span class="line">				<span class="keyword">if</span>(up&lt;upLimit) &#123;</span><br><span class="line">					up=upLimit;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (Exception e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				up = i.getRow();</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				down = i.getRow()+cicleNum;</span><br><span class="line">				<span class="keyword">if</span>(down&gt;downLimt) &#123;</span><br><span class="line">					down = downLimt;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (Exception e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				down = i.getRow();</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				left = i.getColumn()-cicleNum;</span><br><span class="line">				<span class="keyword">if</span>(left&lt;leftLimit) &#123;</span><br><span class="line">					left = leftLimit;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (Exception e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				left = i.getColumn();</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			<span class="keyword">try</span> &#123;</span><br><span class="line">				right = i.getColumn()+cicleNum;</span><br><span class="line">				<span class="keyword">if</span>(right&gt;rightLimit) &#123;</span><br><span class="line">					right=rightLimit;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125; <span class="keyword">catch</span> (Exception e) &#123;</span><br><span class="line">				<span class="comment">// <span class="doctag">TODO:</span> handle exception</span></span><br><span class="line">				right = i.getColumn();</span><br><span class="line">			&#125;</span><br><span class="line">			<span class="comment">//记录栅格周边是否有非内部点，没有的话则圈数+1</span></span><br><span class="line">			<span class="keyword">boolean</span> flag = <span class="keyword">false</span>;</span><br><span class="line">			<span class="comment">//从最左最上开始遍历,遍历顺序从左至右，从上到下</span></span><br><span class="line">			<span class="keyword">for</span>(<span class="keyword">int</span> row=up;row&lt;down;row++) &#123;</span><br><span class="line">				<span class="keyword">for</span>(<span class="keyword">int</span> col=left;col&lt;right;col++) &#123;</span><br><span class="line">					<span class="comment">//判断是否为中心点,即i点,是就跳过</span></span><br><span class="line">					<span class="keyword">if</span>(row==i.getRow() &amp;&amp; col==i.getColumn()) &#123;</span><br><span class="line">						<span class="keyword">continue</span>;</span><br><span class="line">					&#125;</span><br><span class="line">					<span class="comment">//判断是否是内部点，如果是内部点就直接跳过</span></span><br><span class="line">					<span class="keyword">if</span>(data[row][col].getType()!=type.internal) &#123;</span><br><span class="line">						flag = <span class="keyword">true</span>;</span><br><span class="line">						<span class="comment">//计算最小距离</span></span><br><span class="line">						<span class="keyword">double</span> dis = calculateDis(disType, i, data[row][col]);</span><br><span class="line">						disList.add(dis);</span><br><span class="line">					&#125;</span><br><span class="line">				&#125;</span><br><span class="line">			&#125;</span><br><span class="line">			<span class="comment">//当前圈数内未发现非内部点</span></span><br><span class="line">			<span class="keyword">if</span>(!flag) &#123;</span><br><span class="line">				cicleNum++;</span><br><span class="line">			&#125;<span class="keyword">else</span> &#123;</span><br><span class="line">				<span class="comment">//已经发现了非内部点，循环结束</span></span><br><span class="line">				<span class="keyword">break</span>;</span><br><span class="line">			&#125;</span><br><span class="line">			</span><br><span class="line">			</span><br><span class="line">		&#125;</span><br><span class="line">		<span class="comment">//当前栅格搜索完毕,获取到最近非内部点的距离</span></span><br><span class="line">		<span class="keyword">if</span>(!disList.isEmpty()) &#123;</span><br><span class="line">			<span class="keyword">double</span> min = Collections.min(disList);</span><br><span class="line">			i.setNearDis(min);</span><br><span class="line">		&#125;</span><br><span class="line">	&#125;</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>

<p><img src="" alt="点击并拖拽以移动"></p>
<h2 id="测试结果：-1"><a href="#测试结果：-1" class="headerlink" title="测试结果："></a>测试结果：</h2><p>原始数据：</p>
<p><img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205638.png!blog" alt="20190907205638"><img src="" alt="点击并拖拽以移动"></p>
<p>距离变换细化一次：</p>
<p><img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205630.png!blog" alt="20190907205630"><img src="" alt="点击并拖拽以移动"></p>
<p>距离变换细化2次</p>
<p><img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205601.png!blog" alt="20190907205601"><img src="" alt="点击并拖拽以移动"></p>
<p>。。。</p>
<p>n次</p>
<p><img src="https://zhong-blog.oss-cn-shenzhen.aliyuncs.com/blog/20190907205548.png!blog" alt="20190907205548"><img src="" alt="点击并拖拽以移动"></p>

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